Strengthening the Reporting of Genetic Risk Prediction Studies: The GRIPS Statement

Abstract

on behalf of the GRIPS Group T he recent successes of genome-wide association studies and the promises of whole genome sequencing fuel interest in the translation of this new wave of basic genetic knowledge to health care practice. Knowledge about genetic risk factors may be used to target diagnostic, preventive, and therapeutic interventions for complex disorders based on a person's genetic risk, or to complement existing risk models based on classical nongenetic factors, such as the Framingham risk score for cardiovascular disease. Implementation of genetic risk prediction in health care requires a series of studies that encompass all phases of translational research, 1,2 starting with a comprehensive evaluation of genetic risk prediction.With increasing numbers of discovered genetic markers that can be used in future genetic risk prediction studies, it is crucial to enhance the quality of the reporting of these studies, since valid interpretation could be compromised by the lack of reporting of key information. Information that is often missing includes details in the description of how the study was designed and conducted (eg, how genetic variants were selected and coded, how risk models or genetic risk scores were constructed, and how risk categories were chosen), or how the results should be interpreted. An appropriate assessment of the study's strengths and weaknesses is not possible without this information. There is ample evidence that prediction research often suffers from poor design and bias, and these may also have an impact on the results of the studies and on models of disease outcomes based on these studies. [3][4][5] Although most prognostic studies published to date claim significant results, 6,7 very few translate to clinically useful applications. Just as for observational epidemiological studies, 8 poor reporting complicates the use of the specific study for research, clinical, or public health purposes and hampers the synthesis of evidence across studies.Reporting guidelines have been published for various research designs, 9 and these contain many items that are also relevant to genetic risk prediction studies. In particular, the guidelines for genetic association studies (STREGA) have relevant items on the assessment of genetic variants, and the guidelines for observational studies (STROBE) have relevant items about the reporting of study design. The guidelines for diagnostic studies (STARD) and those for tumor marker prognostic studies (REMARK) include relevant items about test evaluation; the REMARK guidelines also have relevant items about risk prediction. 5,10 -12 However, none of these guidelines are fully suited to genetic risk prediction studies, an emerging field of investigation with specific methodological issues that need to be addressed, such as the handling of large numbers of genetic variants (from 10s to 10 000s) and flexibility in handling such large numbers in analyses. We organized a two-day workshop with an international group of risk prediction researchers, epidemiolo...

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

“…37 Furthermore, TRIPOD is also not intended for impact studies that quantify the impact of using a prediction model on participant or doctors' behaviour and management, participant health outcomes, or cost-effectiveness of care, compared with not using the model. 13 38 Reporting guidelines for observational (the STrengthening the Reporting of OBservational studies in Epidemiology [STROBE]), 39 41 studies all contain many items that are relevant to studies developing or validating prediction models. However, none of these guidelines are entirely appropriate for prediction model studies.…”

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement

“…Reporting guidelines for observational (the STrengthening the Reporting of OBservational studies in Epidemiology, STROBE), tumour marker (REporting recommendations for tumour MARKer prognostic studies, REMARK), diagnostic accuracy (STAndards for the Reporting of Diagnostic accuracy studies, STARD) and genetic risk prediction (Genetic RIsk Prediction Studies, GRIPS) studies all contain many items that are relevant to studies developing or validating prediction models. However, none of these guidelines is entirely appropriate for prediction model studies.…”

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker

“…Various reviews have discussed the poor reporting and conduct in the field of clinical prediction modelling 30–35. This has also led to the recent Genetic Risk Prediction Studies (GRIPS) statement to strengthen the reporting and, indirectly, conduct of risk prediction studies with genetic predictors 36 37. Moreover, the number of published prediction models, even for the same disorder or clinical domain, has sharply increased in the last decade 2.…”